The Breast Imaging Reporting and Data System (BI-RADS) and was established by the American College of Radiology as an informal scheme for assigning mammogram screenings into discrete categories of perceived severity: 0-incomplete; 1-negative; 2-benign findings; 3-probably benign; 4-suspicious abnormality; 5-highly suspicious of malignancy; and 6-known biopsy with proven malignancy. A follow-up biopsy is typically recommended for BI-RADS category 4 and higher. However, biopsies ultimately confirm that 70%-80% of BI-RADS 4 designations are benign. Consequently, many women undergo painful and expensive biopsies only to find that the tumor is benign due to the high rate of false positives.
An evolving strategy for the non-invasive interrogation of tumors involves analyzing diagnostic images to identify patterns of appearances that are linked to tumor biology. Imaging analysis provides a non-invasive, low risk approach to assessing tumor biology prior to therapy and an objective pathway for monitoring immunotherapy response.
Using signals detected on image data to characterize tumor biology is based on several factors including: (1) tumor images express underlying tumor biology; (2) growth kinetics and other drivers of oncologic transformation may have unique expression patterns on imaging; (3) unique expression patterns can manifest themselves as imaging phenotypes; and (4) the imaging phenotypes can be characterized both qualitatively and quantitatively. Thus, an understanding of disease biology can be derived, measured, inferred or predicted by examining the imaging phenotype or appearance of a tumor by different radiologic means. This coupled with imaging's ability to provide a comprehensive and real-time assessment of the entire tumor and its micro-environment make quantitative imaging an attractive tool for rapid assessment and prognosis.
Qualitative descriptions of the appearance of tumors on imaging can provide some degree of biologic characterization but are open to interpretation and lack standardization and reproducibility. Although there is general agreement on many qualitative descriptors, reader variability can be broad. Thus, being able to take qualitative features and perform quantitative analysis on imaging is appealing.
The University College in London (UCL) has developed a software platform known as TexRAD that provides quantitative measurements referred to herein as Quantitative Textural Analysis (QTA or TA) of tumor lesions based on conventional (e.g., mammographic) images. QTA as a post-processing technique can be used to quantify tissue complexity by assessing the distribution of textural features (or heterogeneity) within a tumor lesion and their change following treatment. Studies have shown that tumor complexity is seen in multiple imaging modalities and can be derived from many different image types, sequences or imaging series (e.g. CT, MRI, PET, and Mammography).
Tumor complexity can be quantified by QTA using a range of measurable parameters based on enhancement characteristics and/or density changes on a local level by clustering small groups of pixels together using filter kernels (referred to as spatial scale filters (SSF)) within a lesion itself. The output from the analysis then provides a measure of tumor heterogeneity. However, much of the heterogeneity visible on a displayed image can represent photon noise, which tends to mask or suppress the signal strength of underlying biologic information. By first filtering out the noise, QTA analysis can then be used to more effectively probe the biological diversity inherent in tumor complexity.
Notwithstanding the potential for QTA as a tool for deriving imaging biomarkers, a reliable signature for differentiating between malignant and non-malignant BIRADS 4 mammographic lesions remains elusive.
Methods and apparatus are thus needed which overcome the limitations of the prior art.
Various features and characteristics will also become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and this background section.